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Título

Two-Leak Isolation in Water Distribution Networks Based on k-NN and Linear Discriminant Classifiers

AutorRodríguez-Argote, Carlos Andrés; Begovich-Mendoza, Ofelia; Navarro-Díaz, Adrián; Santos-Ruiz, Ildeberto CSIC ORCID; Puig, Vicenç CSIC ORCID; Delgado-Aguiñaga, Jorge A.
Palabras claveDiscriminant analysis
k-NN classification
Leak diagnosis
Machine learning
Water distribution network
Fecha de publicación1-sep-2023
EditorMolecular Diversity Preservation International
CitaciónWater 15(17): 3090 (2023)
ResumenIn this paper, the two-simultaneous-leak isolation problem in water distribution networks is addressed. This methodology relies on optimal sensor placement together with a leak location strategy using two well-known classifiers: k-NN and discriminant analysis. First, zone segmentation of the water distribution network is proposed, aiming to reduce the computational cost that involves all possible combinations of two-leak scenarios. Each zone is composed of at least two consecutive nodes, which means that the number of zones is at most half the number of nodes. With this segmentation, the leak identification task is to locate the zones where the pair of leaks are occurring. To quantify the uncertainty degree, a relaxation node criterion is used. The simulation results evidenced that the outcomes are accurate in most cases by using one-relaxation-node and two-relaxation-node criteria.
Versión del editorhttps://doi.org/10.3390/w15173090
URIhttp://hdl.handle.net/10261/351227
DOI10.3390/w15173090
E-ISSN2073-4441
Aparece en las colecciones: (IRII) Artículos




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